This document provides an overview of network analysis and its applications. It discusses the origins and history of network study in fields like graph theory and sociology. Various network patterns and metrics are described, including density, distance, centrality, and structural measures. Case studies are presented on using network analysis to understand expertise management, trust, and performance issues in organizations. The document emphasizes that network analysis can provide insights through metrics and visualization to inform important business and organizational questions.
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Origins of Network Study
• Graph theory
– Euler, the seven bridges
of Königsberg (1736)
• Sociometry
– Jacob Moreno, Hudson
Training School for Girls
(1932)
3
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Symposium on Social Networks: Dartmouth, 1975
http://eclectic.ss.uci.edu/~drwhite/Networks/MSSB1975.html
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2007
Network Theory Reaches the Business World
2002
2002
2002
2003
2004
2004
5
2005
2009
2009
2002
2002
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Networks of Companies
8
Source: Laurie Lock Lee, http://www.optimice.com.au
Equipment Manufacturers
Systems integrators
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https://kumu.io/UnLtdUSA/austin-social-entrepreneurship
People and Companies
9
Austin Social Entrepreneurship
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Mapping Ideas and Topics
10
http://www.smrfoundation.org/2009/09/12/networks-in-the-news-news-dots-on-slate/
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The Premise: Networks Matter
• Social Capital
– People with stronger personal networks are
more productive, happier, and better
performers
– Companies who know how to manage
alliances are more flexible, adaptive and
resilient
– Our personal health and well-being is often
tied to our social networks
• Making Sense
– Once we have the distinction “network”
then we can use our knowledge of the
networks we live in to make sense
12
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The Opportunity: Leverage the Science
13
• Graph theory provided the
underlying math and science to
help us make sense of the
network structure
• The structure of a network
provides insights into network
patterns:
• About the structure of the
network
• About people in the network
• Once you understand the
structure, you can make
decisions about how to manage
the network’s context – this is
Net Work
14. I’ve become convinced that understanding
how networks work is an essential 21st
century literacy.
Howard Rheingold
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The Importance of Understanding Networks
15
Burt, Ronald S. and Don Ronchi, Teaching executives to see social capital: Results from a field
experiment http://faculty.chicagobooth.edu/ronald.burt/research/files/TESSC.pdf
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The Two Parts
―The language of networks
―Networks in organizations
16
Social Network Analysis:
Cases and Concepts
Mapping Networks: Tools
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The Business Case
18
Management Practice Business Need
Talent Management Finding the natural leaders in the organization
Innovation Identify boundary crossers
Ensure organization has access to new ideas
Collaboration Finding gaps in knowledge flow within groups,
or across organizations or geographies
Monitor or measure changes
Knowledge
management
Identify and retain vital expertise
Monitor or measure changes in k. exchange
Organizational Change
and Development
Identifying opinion leaders for change
management initiatives or during integration
following mergers and acquisitions
Organizational
Performance
Diagnosing cohesion among team members
and targeting critical connections for
improvement
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Rob Cross’s Classic Case: A Performance Issue
19
From: The Organizational Network Fieldbook, Rob Cross et al, Jossey-Bass 2010
Where are the most frequent information flows?
Formal Structure Informal Structure
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A Classic Case
20
From: The Organizational Network Fieldbook, Rob Cross et al, Jossey-Bass 2010
Formal Structure Informal Structure
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A Classic Case
From: The Hidden Power of Social Networks, Rob Cross and Andrew Parker, Harvard Business School Press, 2004
21
From: The Organizational Network Fieldbook, Rob Cross et al, Jossey-Bass 2010
Formal Structure Informal Structure
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A Classic Case
22
From: The Organizational Network Fieldbook, Rob Cross et al, Jossey-Bass 2010
Formal Structure Informal Structure
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A Classic Case
23
From: The Organizational Network Fieldbook, Rob Cross et al, Jossey-Bass 2010
Formal Structure Informal Structure
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What Factors Influence Connections?
• Homophily: Birds of a
feather, flock
together
• Propinquity: Those
close by, form a tie
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Elements in a Network Diagram
25
• A network diagram shows a
collection of entities (nodes) linked
by a type of relationship
(represented by an edge) Nodes
Edges
Node: Vertex, Alter
Edge: Tie, connection, link
Network diagram: graph, sociogram
Synonyms
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Nodes Have Attributes
• Information from survey and/or
HR data*:
– Organizational unit
– Job title/role
– Location
– Expertise
– Job level
– Age
– Gender
• Additional attributes may come
from the survey data itself
26
*within the bounds of what is legal and appropriate
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About Edges
27
• Edges (and the graph as a whole)
are either:
• Undirected (merely connected)
• Directed (edges go “from-to”)
• Reciprocity sometimes matters
Undirected
Node: Vertex, Alter
Edge: Tie, connection, link
Network diagram: graph, sociogram
Synonyms
Directed
Reciprocal
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Edges Define the Shape of the Network
28
• In a survey we might ask:
• “I get information from this
person”
• “I socialize with this person”
• “I think this person is an expert”
• “I go to this person when I have an
idea I want to explore”
• In looking at data, we might want to
find out:
• People who responded to each
others’ emails
• People who attended the same
meetings or who appeared at the
same event – or in the same scene!
In creating a social network diagram, we define what we mean by an edge
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Weights and Tie Strength
29
• Edges may have values, or
weights, associated with them. For
example the difference between:
• Exchanging a few emails
• Being best friends
• The strength between two nodes
may also reflected having multiple
relationships:
• Exchange information
frequently AND
• Socialize AND
• Share trusted information
Node: Vertex, Alter
Edge: Tie, connection, link
Network diagram: graph, sociogram
Synonyms
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Edge Data from Surveys
30
• Surveys:
– Edge data may or may not
be weighted
– People may answer
questions about everyone
in the network or
nominate people they
communicate with, seek
advice from, etc.
• Weighted questions may
denote frequency or
some kind of
strength
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How Are We Managing Expertise?
Acknowledged Expert
Colleague
Questions visualized on the map:
1. Whom do you turn to for professional
advice regarding your daily work?
2. Who is the most acknowledged professional in your field?
Source: Maven7/Orgmapper
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How Are We Managing Expertise?
Accessible knowledgeAcknowledged Expert
Colleague
Group with no
direct access to a
knowledge center
Questions visualized on the map:
1. Whom do you turn to for professional
advice regarding your daily work?
2. Who is the most acknowledged professional in your field?
Non-accessible
knowledge
Source: Maven7/Orgmapper
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How Are We Managing Expertise?
Acknowledged Expert
Colleague
Cluster with no
direct access to a
knowledge center
Questions visualized on the map:
1. Whom do you turn to for professional
advice regarding your daily work?
2. Who is the most acknowledged professional in your field?
Source: Maven7/Orgmapper
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California Computer
35
From “Informal Networks: The Company”
David Krackhardt and Jeffrey R. Hanson
HBR, 1993
CEO Leers must choose someone to lead a strategic task force.
Bair
Stewart
Ruiz
O'Hara
S/W Applications
Harris
Benson
Fleming
Church
Martin
Lee
Wilson
Swinney
Huberman
Fiola
Calder
Field Design
Muller
Jules
Baker
Daven
Thomas
Zanados
Lang
ICT
Huttle
Atkins
Kibler
Stern
Data Control
Leers
CEO
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California Computer
36
From “Informal Networks: The Company”
David Krackhardt and Jeffrey R. Hanson
HBR, 1993
CEO Leers must choose someone to lead a strategic task force.
Bair
Stewart
Ruiz
O'Hara
S/W Applications
Harris
Benson
Fleming
Church
Martin
Lee
Wilson
Swinney
Huberman
Fiola
Calder
Field Design
Muller
Jules
Baker
Daven
Thomas
Zanados
Lang
ICT
Huttle
Atkins
Kibler
Stern
Data Control
Leers
CEO
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Was Harris a Good Choice?
37
Whom do you
go to for help
or advice?
Field Design
Data Control Systems
Software Applications
CEO
ICT
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Was Harris a Good Choice?
38
Whom do you
go to for help
or advice?
Field Design
Data Control Systems
Software Applications
CEO
ICT
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The Question of Trust
39
Whom would
you trust to
keep in
confidence
your concerns
about a work-
related issue?
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The Question of Trust
40
Whom would
you trust to
keep in
confidence
your concerns
about a work-
related issue?
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The Question of Trust
41
Whom would
you trust to
keep in
confidence
your concerns
about a work-
related issue?
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Network Patterns
Multi-Hub
Clustered Core/Periphery
42
Hub and Spoke
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Core/Periphery
43
Core
Periphery
Structural
Hole
Isolates
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It’s all about Questions
44
Patterns provide
insights that provoke
good questions.
Full stop.
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• Look at the whole network
and its components
Network Analysis Also Provides Metrics
• Look at positions of
individuals in the network
Centrality Metrics
Structural (Network) Metrics
45
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Structural Metrics
46
• Common measures:
–Density of interactions
–Distance (average degree of separation)
–Diversity
–Communities, or groups
–Centralization
• Good for comparing questions, groups within
networks or for comparing changes in a
network over time
Look at the whole network and its components
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The Metrics: Density
47
Density. Data provides the percentage of information-getting
relationships that exist out of the possible number that could exist. It
is not a goal to have 100%, but to target the junctures where
improved collaboration could have a business benefit.
Percent of connections that exist out of the total possible
Low Density
High Density
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Impact on Business of Connectivity
• Bank management was
trying to understand the
differences across branches
in sales at credit and
deposit figures
• Using network analysis, the
bank was able to
understand where to direct
mentoring and “best
practice” exchanges across
banks
48
Figures show the performance differences in bank
branches based on the density of their relationships
Total credit /
person
Total deposit /
person
Low density
branches
High density
branches
Low density
branches
High density
branches
Source: Maven7/Orgmapper
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Metrics help reveal diversity within networks
SmA Ops PL A PL B PL C LgA
10 5 8 8 9 10
Small Accounts 72% 2% 11% 0% 2% 5%
Operations 4% 85% 10% 5% 7% 12%
Product Line A 8% 3% 77% 0% 1% 4%
Product Line B 0% 13% 2% 73% 0% 17%
Product Line C 2% 16% 1% 3% 54% 17%
Large Accounts 2% 18% 5% 16% 12% 73%
Density. Data provides the percentage of information-getting
relationships that exist out of the possible number that could exist. It
is not a goal to have 100%, but to target the junctures where
improved collaboration could have a business benefit.
The diagonal shows the interconnectivity among groups in the
organization
Off-diagonal, the metrics illustrate the extent to which people are
reaching across organizational boundaries
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Tracking Metrics Over Time
50
2010
2011
Year # Density Degree
2009 55 2.2% 1.2
2010 90 2.7% 2.4
2011 85 5.3% 4.5
2012 82 8% 6.88
2009
2012
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Structural Metrics: Distance
51
Maximum number of steps to get from one node to another: 12
Average number of steps: 5
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Centrality Metrics: Degree
52Based on: https://plus.google.com/+DaveGray/posts/CQRVeKEsUvF
Raw number of connections (undirected network)
6
7
10
Average Degree: 3.28
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Centrality Metrics: In-Degree and Out-Degree
53Based on: https://plus.google.com/+DaveGray/posts/CQRVeKEsUvF
Number of in-coming and out-going connections
Outdegree = 7
Indegree = 5
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Centrality Metrics: Betweenness
54Based on: https://plus.google.com/+DaveGray/posts/CQRVeKEsUvF
How many paths does a single node lie on?
855
1080
785
793
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Centrality Metrics: Betweenness
Highest Bee-tweenness?
https://www.timeshighereducation.com/sites/default/files/styles/the_breaking_news_image_style/public/bees_teamwork.jpg
h/t: Valdis Krebs
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Centrality Metrics: Closeness
56Based on: https://plus.google.com/+DaveGray/posts/CQRVeKEsUvF
Able to reach all the other nodes in the fewest steps
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Using Metrics: Finding Key Opinion Leaders
57
Source: Maven7
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Using Metrics: Finding Key Opinion Leaders
58
Source: Maven7
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Using Metrics: Finding Key Opinion Leaders
59
Dunbar’s number: 150
• Strong ties:
– Close, frequent
– Reciprocal
– May be embedded in a
strong “local network”
• Weak ties
– Infrequent interaction
– Likely embedded in other
(diverse) networks
– Accessible as needed
Source: Maven7
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Centrality Metrics: Brokerage, Closure
60Based on: https://plus.google.com/+DaveGray/posts/CQRVeKEsUvF
Working cross-cluster or within clusters?
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Centrality Metric: Eigenvector
61
Connected to well-connected nodes
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Putting Some Metrics Together
62
http://qz.com/650796/mathematicians-mapped-out-every-game-of-thrones-relationship-to-find-the-main-character/
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Which Technology Scout is Most Successful?
63
It's Whom You Know Not What You Know: A Social Network Analysis Approach to
Talent Management, Eoin Whelan, SSRN: http://ssrn.com/abstract=1694453
Technology Scout
Connector
Gatekeeper
Group member
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Using Metrics: Ego Networks and Diversity
• Organization
• Expertise
• Age, Tenure
65
External/Internal Ratio: Proportion of an
individual’s ties that are in the same
demographic cohort as the individual
node (“ego”). Ranges from +1 (all
external) to -1 (all internal)
AB’s E/I index: .308
DC’s E/I index: -.714
Can be derived from any demographic:
• Social Ties
• Geographic location
• Hierarchical position
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The Importance of Diversity
People who live in the intersection of social worlds are at
higher risk of having good ideas. – Ron Burt
66
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Organizational Networks Summary
67
• The science of networks has brought insights into the structure
of organizational networks
• Organizational network analysis lets us map relationships to:
• Identify patterns of connection, disconnection, and flows
of knowledge and ideas
• Understand the roles that individuals play and their
potential for enhancing organizational effectiveness
• Developing and sharing maps and metrics helps organizations
to ask good questions and design targeted interventions
• A map represents a moment in time; when maps are shared
the relationships start to shift
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Interventions: Net Work
Ways to change patterns in networks Practices from the KM/OD Repertoire
Create more connections Make introductions through meetings and webinars, face-to-face events
(like knowledge fairs); implement social software or social network
referral software; social network stimulation
Increase the flow of knowledge Establish collaborative workspaces, install instant messaging systems,
make existing knowledge bases more accessible and usable
Discover connections Implement expertise location and/or; discovery systems; social
software; social networking applications
Decentralize Social software; blogs, wikis; shift knowledge to the edge
Connect disconnected clusters Establish knowledge brokering roles; expand communication channels
Create more trusted relationships Assign people to work on projects together
Alter the behavior of individual nodes Create awareness of the impact of an individual’s place in a network;
educate employees on personal knowledge networking
Increase diversity Add nodes; connect and create networks; encourage people to bring
knowledge in from their networks in the world
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What Sorts of Tools Are There?
Category of Tool What you need to know
Expert/Researcher Mapping
and Analysis Tools
Range in complexity of
function and cost
Emerging Platforms Network diagrams can be
shared on the web
Consulting Vendors Specialized solutions with
project life cycle
management
Mapping social metadata Email and log file analysis
Personal network
assessment
DIY or $$$
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Data Flow
Analysis
& Mapping
Tools
Maps
Metrics
Edge Data
UCINET
NetDraw
InFlow
NodeXL
Collection
Tools
Spreadsheets
Online Surveys
Paper
Node Data
Social Media
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ONASurveys
• Specifically designed for doing network analysis
• Demographic questions as well as network relationship
questions
• Users respond to network questions only about people they
indicate they know
• Outputs datasets for:
– NetDraw/UCINET
– NodeXL
– Gephi
74
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Tool Basics – the Dataset (0s and 1s)
75
Information about the nodes (vertices) and the ties (edges)
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https://kumu.io/UnLtdUSA/austin-social-entrepreneurship
Kumu is Based on Community
84
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Emerging Platforms: Polinode
• Create and
manage
surveys
• Upload and
manage
networks
85
https://polinode.com/
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Quick Comparison
Feature/Capability Kumu Polinode
Create and manage surveys No Yes; cost is based on # of survey
respondents and # of names listed
Metrics Yes Yes
Control of colors, shapes, sizes
& overall diagram
GUI and CSS
Stylesheets
Via GUI and specializing attributes
Publish maps on the web Yes Yes
Share data and mapping Yes Yes
Public network pricing Free • Free with basic metrics, up to
250 nodes and 1,000 edges
• $20/month for advanced metrics
and up to 50,000 nodes
Private network pricing (per
month)
$23 (3 projects)
$34 (5 projects)
$49 (10 projects)
$29
User community Yes Yes
86
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Network Insights Don’t Require Fancy Software
• If it’s a network, you can draw it.
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Mapping from Social Media
• Social network platforms:
– A Facebook Friend
– A LinkedIn Connection
– A Twitter Following
• Social media content platforms:
– Likes, posts, replies, shares,
and uploads
– Mentions or “retweet”
#hashtags
• In-house:
– Email
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Twitter Networks in NodeXL: Patterns
89
Polarized Crowd Tight Crowd Brand Clusters
Community Clusters Broadcast Networks Support Network
http://www.pewinternet.org/2014/02/20/mapping-twitter-topic-networks-from-polarized-crowds-to-community-clusters/
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Networks in Social Media
1. Krugman tweets a
link to an article
2. There are a
number of
Tweeters who
publish links to
the article but
these are not
connected to
other Tweeters
3. There are two
densely
interconnected
groups of people
who share the
link and discuss it
90
Analyzing Twitter networks with NodeXL: Broadcast Networks
http://www.pewinternet.org/2014/02/20/mapping-twitter-topic-networks-from-polarized-crowds-to-community-clusters/
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Swoop Analytics
• Use interaction data to
create and analyze
edges in the network
• External/internal ratios
• Edges & reciprocal
edges
92
Personal and Enterprise-level dashboards
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SWOOP User Characterization
• Using the metrics showing
give/receive balance,
SWOOP can provide
feedback on typical user
communication personas
• Using overall metadata,
SWOOP can provide
benchmark information on
an organization’s online
collaboration engagement/
adoption
93
http://www.swoopanalytics.com/index.php/benchmarking/
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Consulting Vendor Options
Vendor If you are looking for… Working with Them
Maven7
OrgMapper
Complete project management of large scale (10,000’s
employees) analysis for Change Management or
Organizational Performance initiatives
Licensing is per survey, based on #
of participants and whether or not
you are certified and doing the
project with them in consultation.
Syndio Social Change Management
Talent Management
Communications Impact
Be their “customers for life” – bring
in the tool, develop expertise and
use it throughout the enterprise to
manage large-scale change.
DNA-7 Organizational Design
Talent Management
Leadership and Collaboration
Projects are one-off at this point.
Keynetiq A tool that provides 12 different survey templates,
analytics, and interactive network maps with
members’ profiles that employees can navigate and
use to search for expertise.
Monthly fee based on number of
people in the company. Custom
pricing for networks with more
than 1000 employees. Also
available ONA consulting, study
design and coordination, and full
ONA project management.
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Maven7 OrgMapper
• Methodology embedded in
the analysis and mapping
tools
– Change management (Influence)
– Organizational performance
(Excellence)
• Customizations managed
through the consulting
services
96
Customized surveys and reports
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Syndio Social
97
Syndio Social Uses SNA to Build Management Dashboards
97
Highest social capital
Most favorable to change
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What to Consider in Selecting Tools
• How often will you do this in-house?
– If you want this to be an organizational competency, then you will want to
designate one or more people to learn to use the tools
– If you designate someone, will it be a data junkie (who will want the DIY
tools) or an organizational expert with solid computer expertise?
– If you want to do this on an occasional basis, then a consultant may be
the right choice
• How much flexibility do you need?
– Do you want to run a range of metrics and dig into the data yourself or
are you comfortable with using a standard set of metrics provided by a
vendor?
99
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Summary
100
• Social network analysis tools and methods are available to map
organizational as well as your individual, personal network
• The tools matter less than the network mindset – and the understanding
that the structure of a network matters
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http://about.me/pattianklam
• 30 years in software engineering
• 10 years in professional services knowledge management &
methodology (Digital, Compaq, Nortel)
• Independent consultant 14 years; thought leader in knowledge
management and social network analysis
• Charter member of Change Agents Worldwide
101